Lane detection using smoothing spline

In vehicle safety research area, a Lane Departure Warning System (LDWS) is of a major interest. The system, however, needs lane detection and lane tracking as basis. This paper proposes an algorithm used to detect the lane as an initialization for lane tracking. The algorithm takes an image captured from a video stream as an input. It then segments the image into a number of small tiles and applies the Principle Component Analysis (PCA) to each tile in order to find the centroid and the principle axis. After recovering the original image from all of the tiles, the probable lines are found using k-means clustering techniques. Two out of these lines will be selected to be the lanes of the road. At the end, the corresponding centroid points are chosen to be represented as control points of smoothing splines represented the lane. This obtained splines are aimed to be used further as an initialization of the lane tracking algorithm. The method has been tested and worked fine. However, its limitation has also been stated and needed to be improved in the future.